Thrombotic characteristics of extracellular vesicles derived from prostate cancer cells
Bibliographic record
Abstract
BACKGROUND: Prostate cancer (PC) patients in advanced stages of the disease have high risk of blood coagulation complications. The procoagulant molecule Tissue factor (TF), and the fibrinolysis inhibitor plasminogen activator inhibitor-1 PAI-1 play important role in this complication. Extracellular vesicles (EV) shed from cancer cells may contribute to the regulation of TF and PAI-1. The procoagulant activity of EV can be associated with the oncogenic and metastatic characteristics of their cells. METHODS: We have expressed EGFRvIII in DU145 cells to assess the role of this oncogene in the procoagulant activity of EV. The intercellular exchange of TF via EV was assessed by downregulating its expression in DU145 cells using shRNA vector, and determining the transfer of TF via EV enriched with the protein. Two PC cell lines with different metastatic potential were used to assess the correlation between the procoagulant activity of EV and the metastatic potential of PC cells. Photometric assays were used to determine FXa-activity and thrombin generation as indicators for the procoagulant activity of EV. Double-tagged proteinase-activated receptor 1(PAR-1) expressed in CHO cells to assess its activation by EV. RESULTS: The expression of EGFRvIII in DU145 cells led to increased mRNA levels for TF and PAI-1, but the increase in these proteins expression was detected mostly in the EV. EV with enhanced levels of TF protein conferred higher TF procoagulant activity on the acceptor cells by intercellular exchange of this protein. Procoagulant activity of EV, assessed by FXa activity, and thrombin generation, was correlated with the oncogenic and metastatic potential of PC cells. The ability of EV to generate thrombin led to the activation of PAR-1, which was evident by the truncation of tagged-PAR-1. CONCLUSION: The active oncogene EGFRvIII increases the concentration of TF and PAI-1 in EV. The procoagulant activity of EV is associated with the oncogenic and metastatic characteristics of their PC cells. Also, EV may contribute to the high procoagulant activity in the tumour microenvironment by the intercellular exchange of TF. Finally, through the generation of thrombin, EV can activate PAR-1, which evidently contributes to cancer progression, linking the coagulation system to tumor progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".